Intellectual Capital & Firm Performance: An Empirical ...

International Journal of Accounting and Financial Reporting

ISSN 2162-3082

2014, Vol. 4, No. 1

www.macrothink.org/ijafr 238

Intellectual Capital & Firm Performance: An Empirical

Study on the Oil & Gas Sector of Pakistan

Mina Kharal1, Muhammad Zia-ur-Rehman

2

Lecturers, Department of Business Administration,

Faculty of Management Sciences, National Textile University, Faisalabad, Pakistan

E-mail: [email protected],

[email protected]

Muhammad Abrar (Corresponding Author)

Assistant Professor, Department of Business Administration,

Faculty of Management Sciences, National Textile University, Faisalabad, Pakistan

Email: [email protected]

Muhammad Sarfraz Khan

Lecturer, Heritage International College, University of South Asia, Lahore, Pakistan


Maria Kharal

Finance manager, Cure to Children, Islamabad


Accepted: June 02, 2014

DOI: 10.5296/ijafr.v4i1.5759 URL: http://dx.doi.org/10.5296/ ijafr.v4i1.5759

Abstract

Knowledge has become power now a days and organization in the ever changing world now

a day consider knowledge and intellect of tier employees as a competitive edge which enables

such organizations to compete effectively in the marketplace. The literature in the domain of

intellectual capital management has received considerable evidence as to whether the

intellectual capital contributes towards the firm performance and value or not. This study


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extends the evidence in this regard by conducting research on Oil & Gas sector of Pakistan.

Using VAIC model of intellectual capital measurement and ROA, ROE, EPS, Sales growth

and M/B ratio as proxies of internal and external performance of the company this study

documents a positive impact of intellectual capital on the organizational performance and

value in the Oil & Gas sector of Pakistan. Thus, intellectual capital could be considered an

intangible asset and spending with regard to the development and establishment of

intellectual capita should be considered asset with long term value. Recommendations and

implications of the study are also provided in the end.

Keywords: Intellectual capital, Firm performance, Oil and Gas sector

1. Introduction

Business environment has considerably been changed in past few decades. The mounting

competition is the main characteristic within every industry and organizations need to cope

up with this intense competition by building up core competencies which previously were not

considered that important. The focus of the corporations is also shifting from the production

to service business around the globe and importance of intangibles has also increased.

Customers now demand innovative products and services which have the ability to surprise

them which is not possible without innovation and research and development. In this context

organizations are recognizing the importance of managing all of their resources particularly

their human resource which is considered key driver of the innovation of any organization.

This human capital management is now considered an unbeatable competitive advantage for

any of the organization and superior performance of the human capital is considered a

guarantee to future sustainability and success of the organization. Thus, it is the need of the

era that organizations maximize their value through efficient utilization of their human or

intellectual capital thus, as a consequence organizations are increasing their investments in

the intangible assets and importance of tangible assets is being declined (Roos, Pike

&Fernstrom, 2012).

Debate as to how this intellectual capital should be measured and quantified is raging and

despite certain development, researchers have failed to build consensus in this regard (See

Bontis, 1998; Pulic, 2004). Apart from that the causal link as to how intellectual capital could

contribute towards the value of the firm is still not clear and this particular aspect has gained

considerable research attention whereby many researchers have tried to assess the extent to

which intellectual capital contributes towards the performance of the organization (Pennings,

Lee &Witteloostuijn1998; Becker, Huselid& Ulrich, 2001; Ali, Akhter, Afzal and Zia, 2010;

Makki, 2010). This study also contributes to the existing evidence in this regard by

conducting an empirical study to determine the impact of intellectual capital on the

performance of the firm in the Oil & Gas sector of Pakistan.

1.1. Objectives of the study

This study is being conducted for the Oil and Gas sector of Pakistan and aims at following

objectives:


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- The core objective of the study is to understand and determine the value of intellectual

capital in terms of organizational performance in Oil & Gas sector of Pakistan.

- The other objectives of the study include to highlight the importance of the

intellectual capital as a driver of value of the firm and to provide policy implications

and recommendations for the better management of intellectual capital.

1.2. Significance of the study

Pakistan is a developing country which has a small stock market. Oil & Gas sector is

considered a primer sector of Pakistani stock market which has been performing very well

from the beginning. The segment of corporate sector is also quite mature and investors prefer

to invest in the stocks of the companies in this sector as these companies are considered

among the blue chip companies of Pakistani stock market. Thus, it is an ideal sector to

explore whether the performance of this sector is explained by the intellectual capital

possessed by the companies of this sector.

This study has dual contribution as it not only provides the empirical evidence in the domain

of a hot research area for a developing country like Pakistan where draught of knowledge and

related evidence is prevailing but also it also has practical value in context of human resource

development and its implications. The established relationships in this study would guide the

practitioners and human resource managers as to how much valuable human resource of an

organization could be and how more value could be ascertained by managing this particular

resource.

2. Literature review

Literature review provides the summaries of the studies which are conducted to establish the

relationship between intellectual capital and firm performance around the world. It would be

more elaborative to provide a derailed summary of each study conducted within this domain

of research. The studies are organized in chorological order and in the last studies conducted

in Pakistan are provided as to provide insight of the phenomenon in the local context.

Bontis, Keow and Richardson (2000) provided evidence with regard to impact of intellectual

capital on firm performance in both manufacturing and service sector of Malaysia. The study

constructed a theoretical model which proposed the causal link between all three dimensions

of intellectual capital i.e. human capital, structural capital and customer capital. The model

propose the direction of causation from human capital to structural capital and customer

capital and from customer capital to structural capital and in the last structural capital is

proposed to cause firm performance which was measured using various financial and industry

related measures. By conducting survey the study, the study confirms that human capital is

more important with regard to the structural efficiency of business in the manufacturing

sector as compared to services. Apart from that customer capital was also found to have a

significant impact on the structural capital with in both industries i.e. services and

manufacturing and in the last development of the structural domain of any business which is

caused by development of human and customer capital is found to have significant

association with the performance of the firm in both of the industry types.


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Cohen and Kaimenakis (2007) sought to investigate the relationship between intellectual

capital and corporate performance in Greek SMEs which are operating in service sector and

are knowledge intensive. The study built structural model which sought to investigate the

impact of human capital on organizational and customer capital and impact of organizational

capital on customer capital. The study further categorized intellectual assets into categories of

hard, soft and functional assets and proposed a direct impact of these three types of

intellectual assets on firm performance which was measured through after tax profits and

sales per employee of the company. The results of the survey conducted, indicated a direct

impact of human capital on organizational as well as on customer capital. Moreover, hard

intellectual asset measure was found related significantly with profits of the company, while

functional intellectual asset measure was found significant in relation to the sales measure of

performance. The soft intellectual asset measure however, was found insignificant with

regard to performance of the SMEs in Greece.

Kehelwalatenna and Gunaratne (2010) empirically analyzed the impact of intellectual capital

on firm performance and investor response for manufacturing firms and financial sector firms

in Sir Lanka. Intellectual capital was measured using Pulic’s VAIC model by considering

dimensions of human capital, structural capital and capital employed, while performance was

measured using return on equity (ROE) and holding period return (HPR) and investor

response was measured using market to book (M/B) ratio. The results indicated that

intellectual capital is significantly associated with the variables of firm performance and

investor response in both manufacturing firms and financial sector firms.

In anticipation of the increasing interest of the researchers with regard to the measurement

and value of intellectual capital, Veltri (2009) provided meta-analysis as to provide a

synthesis of development relating to the intellectual capital and firm performance. The study

put forwards that the research on the intellectual capital has significantly increased after

development of VAIC model as this model make measurement of constructs related to

intellectual capital with the help of published accounting data. The author argued about the

mediating role of VAIC complements between intellectual capital and financial performance

and indicated towards the inconsistency with regard to the measures that were used by

previous studies to quantify intellectual capital and varying proxies used to measure financial

performance. The moderating effect of human capital with regard to relationship between

intellectual capital and firm performance is quite evident in the literature. Moreover, there

was another problem relating to duality of measurement as some authors measured firm

performance with proxies like Economic Value Added (EVA), Tobin’s Q, Market to Book

(M/B) ratio and other’s used these as proxy of intellectual capital. The Meta analysis overall

indicate that there is considerable theoretical as well as empirical work to be done in the

domain of intellectual capital and its impact on the performance of the firm.

Emadzadeh at al. (2013) provided evidence with regard to the impact of intellectual capital in

firm performance in automobile sector of Iran using survey approach. Intellectual capital was

measured using three dimensions of human capital, structural capital and relational capital

while firm performance was measured using four performance dimensions as proposed by the

Balanced Scorecard performance measurement framework i.e. learning & growth of


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employees, internal business processes, customer satisfaction and financial performance. The

study found a significant and positive impact of intellectual capital as a whole on all four

dimensions of organizational performance.

Chang (2007) empirically elaborated the value of intellectual capital for IT firms in Taiwan.

His study in this regard proposed that IT firms in Taiwan have the ability to transform their

intangibles to high value added products or services. The study modified VAIC model as

proposed by Pulic (2000) by including innovative capital (as measured by research and

development expenses) and protective capital (as measured by intellectual property assets

such like patents, copy rights, trademarks etc.) along with the traditional VAIC dimensions

The performance construct on the other hand was measured using accounting measures of

profit margin. The study indicated that the explanatory power of the modified model is higher

than that of the traditional model of intellectual capital with regard to the explanation of

variation in performance within IT sector of Taiwan. This study overall found that investors

give higher value to firms having grater intellectual capital efficiency as the firms having

grater intellectual capital efficiency yield better profits and market returns.

Muhammad and Ismail (2009) explored the impact of intellectual capital efficiency on the

performance of financial sector firm of Malaysia. By using VAIC to measure intellectual

capital efficiency and ROA along with profitability to measure performance, the study

documents a strong and positive impact of intellectual capital efficiency on the financial

performance of the financial sector of Malaysia. Moreover, it was also found that with in

finical sector banking sector of Malaysia relies more heavily on the intellectual capital

efficiency, which is followed by insurance sector and brokerage firms in a subsequent

manner.

Wang (2011) also tried to investigate the impact of the intellectual capital on the performance

of the firms in Taiwan. Using three dimensional conceptualization of intellectual capital i.e.

human capital, structural capital and customer capital, this research also seeks to add research

and development in the intellectual capital-Firm performance nexus where performance of

the firm was measured using proxies of return on assets, market to book value and total firm

productivity. The research found that Taiwanese firms neglect the human element of

intellectual capital and focus more on the accounting performance aspect of the firms.

Tayles, Pike and Sofian (2007) on the other hand tried to quantify perceptions of the

managers as to whether there exist a causal link between the intellectual capital and

management accounting practices such like risk management, capital budgeting, planning &

control and performance measurement. This research also looks into the ability of firms

having higher intellectual capital to respond to the market and economic changes and that

whether such firms perform better in comparison to other firms or not. Using survey

methodology, the study confirms a better management accounting infrastructure of the firm

having higher intellectual capital capabilities. The evidence provided by the research also

indicate that firms which are driven by intellectual capital are better able to respond to the

changes in the external environment and also have better performance than firm having lower

intellectual capital profile.


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Zehri, Abdelbaki and Bouabdellah (2012) conducted a research in the same phenomenon in

context of Tunisia. VAIC model was used by the study to measure intellectual capital

efficiency, while performance of the organization was seen in context of financial

performance (return on assets), economic performance (operating margin) and market

performance (Market to book ratio). On the whole, this study confirms prevalence of a direct

impact on financial and economic performance of the company. The direct relationship

between intellectual capital and market performance however, was not confirmed by the

study.

Iswati and Anshori (2007) conducted a similar kind of study for the insurance companies

listed in Jakarta Stock Exchange, Indonesia. The study measured intellectual capital by

subtracting average of five year book value of the firm from average of five year market

value of the firm while financial performance of the insurance firm is measured through their

profitability. The study found a positive relationship if intellectual capital with profitability of

insurance companies in Indonesia.

Abdulai, Kwon and Moon (2012) targeted software firms in order to assess the impact of

intellectual capital on their performance in region of West Africa as software companies are

driven be their intellectual capability rather than the physical assets of other capital intensive

firms. By using the intellectual capital classification of human, structural and relational

capital the study used questionnaire approach to validate the impact of intellectual capital on

competitive capabilities and ultimately on the performance of the firm. The study confirms

the direct impact of intellectual capital on both internal and external competitive capabilities

of the firms and also on the performance of the sampled firms. Moreover, transformational

leadership was found to have a partial moderating impact between the relationship of

intellectual capital and both internal and external competitive capabilities of the firms. Part

from the commitment of management also moderated this relationship in a significant manner.

This study overall confirms the propositions of literature advocating the value of intellectual

capital as a competitive advantage and perquisite of performance. Moreover, the role of

management and leadership in channelizing the intellectual capital to build competitive

competencies is also elaborated by this study.

Jalilian, Hassani, Ghanbari, Jalilian and Moradi (2013) took the initiative to conduct a case

study to investigate the impact of intellectual capital on the financial and non-financial

performance of West Cement Company of Kermanshah, Iran. The variable studies in the

research were intellectual capital as measured through human capital, structural capital and

relational capital, organizational leavening capability and firm performance; which were

measured through financial and non-financial performance. The study found an inter-relation

between all three dimensions of intellectual capital. All three dimensions of intellectual

capital also yielded a direct correlation with organizational leaning capability, financial and

non-financial performance

Mavridis (2004) based his study on the banking sector of Japan, Greece and Australia as to

understand the implications of intellectual capital performance. The study used VAIC model

of intellectual capital and hypothesizes a causal link of dimensions of human capital and


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physical capital with value based performance of banks. The study found that banking using

their intellectual capital (human capital) more as compared to their physical capital was

performing considerably better. The study also confirm performance differences among the

organizations representing banking sector of Japan, Greece and Australia and these

differences could be explained through the utilization of the human component of the

intellectual capital.

Yusoff, Jantan and Ibrahim (2003) also investigated the issue by investigating the moderation

of environment and strategy for impact of intellectual capital on firm performance in

Malaysia. The human, structural and social capital was used to conceptualize intellectual

capital and perceptual measures of performance such like overall performance, industry

leadership, technological development, increase in customer base, profitability and revenue

growth. Using survey questionnaire the study found that impact of intellectual capital is more

pronounced on firm performance in dynamic performance as compared to stable environment.

Moreover, impact of intellectual capital on firm performance is also moderated by the type of

strategy being used by the organization. Impact of intellectual capital on the performance of

firm is also stronger for firms pursuing strategies such like segmentation, product diversity

and differentiation than the firms pursuing cost leadership strategy. Thus, it is concluded that

intellectual capital has a role to play in the dynamic environment of today which is getting

complex with time and it could prove to be an effective tool for organizations operating in

hostile environment to better respond to the changing external environment.

Sofian, Tayles and Pike (2011) conducted another study on the elaboration of the benefits of

intellectual capital for Malaysian firms as to establish relationship between different forms

and degrees of intellectual capital and management counting practices particularly corporate

performance and performance measurement. The study also examined whether firms

investing in intellectual capital give more consideration to non-financial measures of

performance or not? The study on the whole found a significant impact of intellectual capital

on corporate performance. Moreover, the firms investing in intellectual capital also tend to

consider non-financial measures for their performance management in Malaysia.

Reed, Lubatkin and Srinivasan (2006) integrated all three dimensions of intellectual capital

i.e. human, organizational and social and hypothesized that each of three dimensions of

intellectual capital exert draws strength from other dimensions with regard to its impact on

the financial performance of the organization. Moreover, the impact of intellectual capital is

also contingent on the external industry condition in which the firm is being operated. Using

the data of banking sector of USA, the study found industry effects in the relationship

between intellectual capital and performance. Moreover, different dimensions of intellectual

capital were found to have an integrated impact on the performance of the banks in USA.

There is also indication that too much intellectual capital could also hinder the performance

of the banks in some cases. The study also argued that banking sector is witnessing

significant technological shifts where human capital is being replaced by technological

capital so in baking industry, managers should consider the appropriateness of investment in

the human capital and technological innovations. This also indicates towards the importance

of industry consideration with regard to the potential that intellectual capital could offer to a


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specific type of organization.

Chen, Chang and Hwang (2005) investigated the role of intellectual capital in value creation

for the firm both in terms of financial and market performance. Using VAIC to measure

efficiency of intellectual capital and market to book ratio as indicator of market performance

along with other ratios of financial the authors elaborated the role of intellectual capital in

value creation for companies listed in Taiwan Stock Exchange. The results indicated a

positive impact of intellectual capital on both financial as well as market performance of the

firms in Taiwan. It was also found that investor may weight three components of intellectual

capital in a different manner. Another study conducted by Ahangar (2011) investigated the

same phenomenon in Iranian corporate sector. The study used VAIC model to measure

intellectual capital efficiency and used profitability, sales growth and employee productivity

as performance proxies. The study indicated that human capital is most important component

of intellectual capital and all three dimensions as proposed by VAIC are significant

explanatory variables for profitability as measured by return in asset. Clarke, Seng and

Whiting (2011) conducted same type of study in Australian business context. Using VAIC

model as proposed by Pulic, the study found a direct impact of intellectual capital and firm

performance and dimensions of capital employed efficiency and to a lesser extent human

capital efficiency are important in this regard. Moreover, Lags of dimensions of intellectual

capital also found to have correlation with performance of firms in Australia. A moderating

impact of physical and financial capital on intellectual capital-firm performance relationship

was also put forward by the study.

The studies presented above are mostly related to the developing economies which are in

close proximity of Pakistani local context. The studies elaborated the concepts using various

operational definitions of intellectual capital, methods and proxies of performance. Most of

the studies indicated towards a direct impact of the various dimensions of intellectual capital

on internal as well as market performance of the organization. Following section provides

theoretical discussion as to elaborate the theoretical relationship between the variables under

consideration.

3. Methodology

This study is conducted in order to see the impact of intellectual capital on the firm

performance thus, following model is specified:

Firm Performance = f (Intellectual Capital)

Or

FPit = β0 + β1ICit + µ

Where,

FP = Firm performance

IC = Intellectual Capital

Firm performance which is the dependent variable is measured using the proxies of ROA,


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ROE, Sales growth and EPS. While intellectual capital is measured using VAIC model

developed by Pulic (1998, 2000). The model provides following procedure to measure

intellectual capital.

VAIC = ICE + CEE

Where

VAIC = Value added intellectual coefficient

ICE = Intellectual capital efficiency

CEE = Capital employed efficiency

So, VAIC is basically sum of these two components i.e. intellectual capital efficiency and

capital employed efficiency and intellectual capital efficiency is further broken down into two

components:

ICE = HCE + SCE

Where

HCE = Human capital efficiency

SCE = Structural capital efficiency

Thus, basically VAIC is additive value of three components i.e. human capital efficiency

(HCE), structural capital efficiency (SCE) and capital employed efficiency (CEE). These

three components of VAIC are calculated as follows:

HCE = VA/ HC

SCE = SC/ VA

CEE = VA/ CE

Where

VA = Value added

HC = Human capital

SC = Structural capital

CE = Capital employed

The above variables of the model are calculated by following procedure:

VA = Output – Input

Where inputs of the organization are represented by its resources and costs and output on the

other hand consistrevenues of the organization. Ståhle, Ståhle&Aho (2011) also provided

another way to calculate the value added:

VA = P + C + D + A


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Where

P = Operating profits of the organization

C = Cost of salaries of employees

D = Depreciation expense

A = Amortization expense

The second important variable used in calculation of VIAC is human capital which is said to

be equal to the costs incurred on the human resource of organization in shape of salaries &

wages. Thus,

HC = C = Cost of employee salaries & wages

The third variable in this regard is the structural capital which is calculated by subtracting

human capital from value added as follows:

SC = VA – HC = P + D + A

Capital employed could also be calculated by subtracting value of intangible assets from total

assets:

CE = TA – IA

Where

TA = Total assets of the organization

IA = Intangible assets of the organization

3.1 Sample selection and data source

Data was collected from the annual reports of companies representing Oil & Gas sector in

Pakistan. According to the list provided by Karachi Stock Exchange, there are 12 companies

listed in the KSE which represent oil and gas sector. The data from the company was

collected for a period of 9 years starting from 2005 to 2013. Some of the companies did not

provided financial reports for some years on their websites thus, a balanced panel could not

be constructed for the study and data collected was organized as pooled data. Total

observations comprising the sample of the study are 78. Thus, on average more than 6 years

data is considered for each company considered in the sample.

3.2 Analysis technique

The primary objective of the study is to assess the impact of the intellectual capital on the

performance of the firm. The data collected for the study is pooled in nature, thus pooled

OLS technique is deemed suitable for the estimation. Moreover, correlation analysis is also

conducted in order to establish primary relationship between the variables and see whether all

proxies of performance correlate significantly in order to further ensure robustness of the

results. SPSS 16 is used for the estimation and related empirical analysis in this research.


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4. Analysis and discussion

The data collected has been analyzed using different statistical tests. First of all descriptive

statistics relating to the variables of the study are presented. After that correlation analysis if

provided and in the end regression analysis is provided in order to establish relationships

between the variables.

Descriptive statistics in the study are used to compare the means and standard deviation of

the variables which are being considered in the study for oil and gas sector. The variables

considered in the study are return on assets (ROA), return on equity (ROE), sales growth,

earning per share (EPS), value added intellectual capital coefficient (VAIC) and market to

book ratio (M/B ratio).

Table 1 provides descriptive statistics of the variables considered in the study for oil and gas

sector of Pakistan. The minimum of the first dependent variable i.e. ROA is -.1897 along with

a maximum of .5572. The mean and standard deviations of the variable are .174569

and .1801 respectively. The minimum and maximum for ROE, on the other hand are -1.6535

and .9995 respectively and mean for the variable is .2979 along with a standard deviation

of .4631. The next variable of the study is sales growth which has minimum of -.5005 and

maximum of 2.4024 along with a mean of .219286 and standard deviation of .3501. EPS is

the next variable in line which has a minimum of -108.78 and a maximum of 159.33. The

mean of the variable on the other hand is 38.034 and a standard deviation of 44.5842. VIAC

has a minimum of -9.12 and maximum of 33.19. The mean average for this variable is

10.6425 along with a standard deviation of 9.1625. The last variable which is considered in

the study is M/B ratio which has a minimum of .66 and maximum of 13.91. The mean

average of the variable is 2.5575 and standard deviation is 1.9929.

Table1. Descriptive Statistics (Oil & Gas Sector)

Minimum Maximum Mean Std. Deviation

ROA -.1897 .5572 .174569 .1800551

ROE -1.6535 .9995 .297901 .4630730

Sales Growth -.5005 2.4024 .219286 .3500587

EPS -108.78 159.33 38.0343 44.58425

VAIC -9.12 33.19 10.6425 9.16251

M/B Ratio .66 13.91 2.5575 1.99291


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Correlation analysis has primarily been used in this study to establish the primary relationship

among variables. Table 2 on the other hand provides correlation matrix for the oil & gas

sector. For oil & gas sector, all the performance variables expect sales growth are

significantly correlated with each other. The correlation however, is moderate between

variables of ROA and ROE and between variables of ROE and EPS. The relationship

between ROA and EPS on the other hand is significant but weak. EPS and M/B ratio also

have a negative weak and significant correlation. All the independent variables expect sales

growth are found to be significant predictors of intellectual capital efficiency in oil & gas

sector of Pakistan.

Table 2 .Correlation Matrix (Oil & Gas Sector)

ROA ROE Sales Growth EPS VAIC

ROE Pearson Correlation .567**

Sig. (2-tailed) .000

Sales Growth Pearson Correlation -.088 -.054

Sig. (2-tailed) .482 .667 0.5line

EPS Pearson Correlation .301**

.505**

-.016

Sig. (2-tailed) .007 .000 .899

VAIC Pearson Correlation .772**

.496**

-.044 .449**

Sig. (2-tailed) .000 .000 .725 .000

M/B Ratio Pearson Correlation .220 -.091 .130 -.297* .248

*

Sig. (2-tailed) .078 .469 .349 .016 .046

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Regression analysis in the study is the final step of analysis which provides the estimation of

the variables by considering performance related variables dependent variables and VAIC as

independent variable. Five models are constructed for the study the first four models consider


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various measures of performance as dependent variables i.e. ROA, ROE, sales growth and

EPS and the last model takes into account the market performance of the firms sampled for

the study by taking market to book ratio as dependent variable.

Model 1: Impact of VAIC on Return on Assets (ROA) in Oil & Gas Sector

Table3 on the next page provides model summary for the regression estimates relating to the

model 1 which sought to establish the impact of VAIC on return on assets (ROA) for the oil

& gas sector of Pakistan. The R square of the model is .596 which is quite good as it

associates more than 50% explanation of variation in ROA with VAIC. The adjusted R square

of the model on the other hand is .591 along with a standard error of .1152.

Table 3.Model Summary (Model 1)

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .772a .596 .591 .1152015

a. Predictors: (Constant), VAIC

Table 4 following provides the ANOVA results of the model 1 which considers ROA as

dependent variable and VAIC as independent variable. The F statistics of the model is

112.098 which is quite good and indicates that model is a good fit at a significance level of

1%. This again ensures the reliability of the estimation.

Table 4. ANOVA (Model 1)

Model Sum of Squares Df Mean Square F Sig.

1 Regression 1.488 1 1.488 112.098 .000a

Residual 1.009 76 .013

Total 2.496 77


b. Dependent Variable: ROA


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Table 5. Coefficients (Model 1)

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) .013 .020 .654 .515

VAIC .015 .001 .772 10.588 .000

a. Dependent Variable: ROA

Table 5 above provides the regression coefficient of the regression model which assumes

ROA dependent variable and VAIC as independent variable. The beta coefficient of VAIC is

found to be .015 along with a t statistics of 10.588 which confirms that VAIC has a positive

and significant impact on return on assets of the firms in oil & gas sector of Pakistan. That

leads us to accept our first hypothesis Ha1 for oil & gas sector; which states there is a positive

impact of VAIC on return on assets.

Model 2: Impact of VAIC on Return on Equity (ROE) in Oil & Gas Sector

Table 6 on provides the model summary of the model 2 which estimates the impact of VAIC

on return on equity of firms in oil & gas sector of Pakistan. R square for the model is

estimated to be .246 which indicates that independent variable i.e. VAIC causes almost 25%

variation in the dependent variable i.e. return on equity. The adjusted R square and standard

error of the model are .236 and .4048 respectively.

Table 6. Model summary (Model 2)


Std. Error of the

Estimate

2 .496a .246 .236 .4048092


Table 7 provides the ANOVA results of the model 2. The F statistics of the model 2 is found

to be 24.76 which indicate that model is a good fit at the significance level of 1%.


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2 Regression 4.057 1 4.057 24.760 .000a

Residual 12.454 76 .164

Total 16.512 77


b. Dependent Variable: ROE

Table 8 provides the beta coefficients of the model 2 which assumes VAIC as independent

variable and return on equity dependent variable. The beta coefficient of VAIC for return on

equity is estimated to be .025 along with a t statistics of 4.976 which indicates that VAIC has

a positive and significant impact on the return on equity. This leads us to accept our second

hypothesis for oil & gas sector; which proposed a positive and significant impact of VAIC on

the variable of return on equity.


Model


Standardized

Coefficients

T Sig. B Std. Error Beta

2 (Constant) .031 .071 .443 .659

VAIC .025 .005 .496 4.976 .000

a. Dependent Variable: ROE

Impact of VAIC on Return on Sales Growth in Oil & Gas Sector

Table 9 provides the model summary for the regression estimating the impact of VAIC on

sales growth. The R square for the model is quite low i.e. .002 indicating towards a low

predictability power of VAIC with regard to dependent variable of sales growth. Adjusted R

square is negative for this model and standard error is .3524.


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Table 9. Model Summary (Model 3)


Std. Error of the

Estimate

3 .044a .002 -.014 .3524400


Table 10 provides the results of ANOVA for the model estimating the impact of VAIC on

sales growth. F statistics for this model is quite low i.e. .125 and indicates that model is not a

good fit.

Table 10.ANOVA (Model 3)


3 Regression .015 1 .015 .125 .725a

Residual 7.950 64 .124

Total 7.965 65


b. Dependent Variable: Sales Growth

Table 11 provides the beta coefficient of VAIC with regard to its impact on the sales growth

of the companies operating in oil & gas sector of Pakistan. It is found that beta coefficient of

the VIAC is -.002 along with a T statistics of -.353 which indicates that the relationship of

VAIC and sales is negative but insignificant that leads towards the rejection of third

hypothesis of the study i.e. Hc1 for oil & gas sector which advocated a positive and significant

impact of VAIC on sales growth of the companies.


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Model


Standardized

Coefficients


3 (Constant) .239 .070 3.422 .001

VAIC -.002 .005 -.044 -.353 .725

a. Dependent Variable: Sales Growth

Model 4: Impact of VAIC on Earning per Share (EPS) in Oil & Gas Sector

Table 12 provides the model summary of the estimation with regard to the impact of VAIC on

earning per share in the oil & gas sector of Pakistan. R square of the model is estimated to

be .201 which indicates that VAIC explains more than 20% variation in earning per share of

the companies in oil & gas sector of Pakistan. Moreover, adjusted R square and standard error

of the model are .191 and 40.108 on a respective sequence.

Table 12.Model Summary (Model 4)


Std. Error of the

Estimate

4 .449a .201 .191 40.10821


Table 13 provides ANOVA results of model estimating the results relating to the dependency

of earning per share on VAIC. The F statistic as provided by ANOVA results is 19.145 which

indicate that model is a good fit at a significance level of 1%.


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4 Regression 30798.329 1 30798.329 19.145 .000a

Residual 122258.836 76 1608.669

Total 153057.165 77


b. Dependent Variable: EPS

Table 14 provides the beta coefficients of model 4 which estimates the impact of VAIC on

earning per share of the company. The coefficient for VAIC is estimated to be 2.183 along

with a t statistic of 4.376 indicating a positive and significant impact of VAIC on earning per

share of the firms under domain of oil & gas sector. Thus, fourth hypothesis of the study Hd1

is accepted which proposed a significant a positive impact of VAIC on earning per share.


Model


Standardized

Coefficients


4 (Constant) 14.804 6.986 2.119 .037

VAIC 2.183 .499 .449 4.376 .000

a. Dependent Variable: EPS

Model 5: Impact of VAIC on Market to Book Ratio (M/B ratio) in Oil & Gas Sector

Table 15 provides the model summary for the regression conducted to see the impact of the

value added intellectual coefficient (VAIC) on market to book ratio (M/B ratio). The R square

of the model is found to be .062 which indicated that VAIC predicts about 6% of the variation

in M/B ratio. The adjusted R square of the model is .047 along with the standard error of

1.94569.


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Table 15. Model Summary (Model 5)


Std. Error of the

Estimate

5 .248a .062 .047 1.94569


Table 16 provides the ANOVA results of the model 5 which assumes M/B ratio to be

dependent variable and VAIC to be independent variable. F statistic of the model is found to

be 4.144 which indicate that model is a good fit at the significance level of 5%.

Table 15.ANOVA (Model 5)


5 Regression 15.688 1 15.688 4.144 .046a

Residual 238.499 63 3.786

Total 254.187 64


b. Dependent Variable: M/B Ratio

Table 16 provides the coefficient results of the regression conducted to see the impact of

VAIC on M/B ratio. The beta coefficient of VAIC for M/B ratio is found to be .065 along

with a t statistic of 2.03 which indicates that VAIC has positive impact on the M/B ratio

which is significant at 5% level of significance. This leads us to accept fifth hypothesis He1

for oil & gas sector which proposed a positive impact of VAIC on M/B ratio.


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Table 16.Coefficients (Model 5)

Model


Standardized

Coefficients


1 (Constant) 1.870 .415 4.502 .000

VAIC .056 .027 .248 2.036 .046

a. Dependent Variable: M/B Ratio

4.1 Discussion

Overall, a positive impact of the intellectual capital as measured through VAIC has been

indicated by this study in Oil & Gas sector of Pakistan. Only insignificant relationship found

in the oil and gas sector was for the variable of sales growth which has yielded an

insignificant beta. The reason for this insignificant impact could be found in the nature of the

industry which is under consideration as Oil & gas sector do not have much of the sales

growth potential as players in the market are quite mature and also the market has been

saturated. The evidence of a significant and positive impact of VAIC on ROA and ROE has

been supported by many previous studies as elaborated by Ståhle, Ståhle&Aho (2011). The

relationship of intellectual capital with EPS is consistent with the theoretical and empirical

explanations provided by the literature (Chang, 2007; Tan, Plowman & Hancock, 2008). The

last dependent variable studied as external performance measure of the organization is M/B

ratio. VAIC has provided evidence of a significant and positive beta with regard to M/B ratio

which is the capability of an organization to create future value. The relationship indicates

that intellectual capital has the potential to create long run value for the organization. This

positive and significant relationship is consistent with the prepositions and empirical findings

provided in the previous studies (See, Pulic, 2000; Bontis& Fitz-enz, 2002; Chen, Chang &

Hwang, 2005).

5. Conclusion

Oil & gas sector is one of the premier sectors of Pakistani stock market which is

characterized by high performance. But pressure on all segments of Pakistani market is

mounting and the need of efficient utilization of the resources has become more prominent in

the recent era of technological innovations where intangible and intellectual assets have

become more important than traditional physical assets. Human capital could be the driving

force of performance in the sector under study and performance of this sector could add value

to the whole economy of Pakistan. Apart from the local issues, knowledge has become power

around the world and knowledge economies are being built and this knowledge is


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increasingly perceived to be the driving force of the economic development of many

developed countries and countries which have ignored this domain are less productive as

Kaplan &Nortorn (2004) argued that countries like Saudi Arabia and Venezuela have

considerably high amount of natural resources, but these countries have ignored the

knowledge and people aspect of their economy and this is the main reason for the lower

productivity of these countries. On the other hand countries like Taiwan and Singapore have

invested in informational and human capital domains in a substantial manner and thus, are

reaping the fruits of high productivity. Thus, human and informational capital not only has

relevance in economic context but also makes a firm more competitive in the hostile

environment of today. In this regard, this study seeks to study the impact of intellectual

capital efficiency on the performance of Oil & Gas sector of Pakistan. The study documents a

significant impact of VAIC on the performance of the firms relating to Oil & Gas sector of

Pakistan.

So, it can reasonably be assessed that better intellectual capital management could lead

towards greater efficiency with regard to the Oil & Gas sector of Pakistan which would not

only be meaningful in individual organizational context but in overall economic context as

well. The study also supports the notion that spending on intellectual and human capital

should be considered investment rather than expenses as these investments a paid off by an

enhanced efficiency of the processes and an improved profitability of the organization. The

theoretical and empirical evidence also supports a positive impact of the intellectual capital

on the value of the firm which is partially supported by this study as well. So, it is concluded

that if a firm is to survive and operate efficiently, it has to invest in and build its intellectual

and human capital as to ensure the long run performance and sustainability of the

organization.

6. Recommendations

On the basis of the findings of the study following suggestions are provided to the various

stakeholders.

- Overall, this study documents a significant impact of intellectual capital efficiency on

both internal and external performance of the organizations working in the sectors

understudy. In this regard, the importance of the intellectual capital should not be

undermined and the mechanism, through which intellectual and human capital flows

should be developed, maintained and improved.

- Management of the organization, specifically human resource managers should

consider all possible means and resources to build a better intellectual and human

work force. They should also consider improvement strategies with regard to

intellectual and human resources of the organizations through training and

development activities.

- More attention should be given to the human side of the intellectual capital and

reliance should not strictly be focused on the numeric evaluation and improvement.

- In order to channelize the human capital in a proper way, support of the organization,


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particularly top management is of utmost importance. This fact should be recognized

and necessary support of the top management should be provided in this regard.

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